EURASIAN JOURNAL OF

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Effects of Smoking on Volume, Conductivity and Scatter Parameters of Leukocytes

Sigara İçiminin Lökositlerin Hacim, İletkenlik ve Saçılma Parametrelerine Etkisi

İbrahim Solak, Aziz Kara, Bahadır Öztürk, İbrahim Güney, Mehmet Ali Eryılmaz

Euras J Fam Med 2020;9(1):9-14. https://doi.org/10.33880/ejfm.2020090102

 

Original Research / Orijinal Araştırma


ABSTRACT

Aim: In this study, we aimed to determine changes in leukocytes volume, conductivity and scatter parameters in smokers compared to non-smokers.

Methods: A total of 117 individuals (45 smokers and 72 non-smokers) were included in the study. While those who smoked at least 10 pack-years were included in the case group, those who never smoked at all were included in the control group.

Results: While there was a statistically significant difference in mean neutrophil volume, mean neutrophil conductivity, mean lymphocyte conductivity, mean lymphocyte scatter, mean monocyte volume, mean monocyte conductivity, mean monocyte scatter, mean eosinophil conductivity values between the two groups, there was no statistically significant difference in mean neutrophil scatter, mean lymphocyte volume, mean eosinophil volume, mean eosinophil scatter values between the two groups.

Conclusion: This study showed that smoking affected volume, conductivity and scatter parameters. Clinicians should consider whether the patient smokes if they want to diagnose any diseases using volume, conductivity and scatter parameters.

Keywords: smoking, leukocytes, conductivity, scattering, neutrophils

ÖZ

Amaç: Bu çalışmada, sigara içenlerde içmeyenlere göre lökosit hacmi, iletkenlik ve saçılma parametrelerinde meydana gelen değişiklikleri bulmayı amaçladık.

Yöntem: Çalışmaya toplam 117 kişi (45 sigara içen ve 72 sigara içmeyen) dahil edildi. En az 10 paket yıl içenler vaka grubuna dahil edilirken, hiç sigara içmeyenler kontrol grubuna dahil edildi.

Bulgular: İki grubun ortalama nötrofil hacmi, ortalama nötrofil iletkenliği, ortalama lenfosit iletkenliği, ortalama lenfosit saçılımı, ortalama monosit hacmi, ortalama monosit iletkenliği, ortalama monosit saçılımı, ortalama eozinofil iletkenliği değerleri arasında istatistiki olarak anlamlı fark var iken, ortalama nötrofil saçılımı, ortalama lenfosit hacmi, ortalama eozinofil hacmi, ortalama eozinofil dağılımı değerlerinde ise istatistiksel olarak anlamlı bir fark bulunmadı.

Sonuç: Bu çalışma sigara içiminin lökosit hacmi, iletkenlik ve saçılma parametrelerini etkilediğini göstermiştir. Klinisyenler, lökosit hacmi, iletkenlik ve saçılma parametrelerini kullanarak herhangi bir hastalığı teşhis etmek istiyorsa hastanın sigara içip içmediğini dikkate almalıdır.

Anahtar kelimeler: sigara içme, lökositler, iletkenlik, saçılma, nötrofiller


Introduction

The prevalence of smoking increases all over the world, especially in developing countries. Smoking poses a high risk for peripheral arterial disease, myocardial infarction, heart failure, stroke, as well as lung, pancreas, kidney, cervical and gastric cancers (1-3). 

Previous studies using various biomarkers have shown that smoking increases systemic inflammation (4-6). 

Although its cause and mechanism are not clearly known, acute smoking leads to an increase in leukocyte, eosinophil and platelet counts in peripheral blood (7). Several studies have indicated that the markers of white blood cell differential count and platelet activity are impaired by smoking (8,9). 

The “volume, conductivity and scatter” (VCS) technology of the COULTER LH 780 Hematology Analyzer (Beckman Coulter, Inc.) measures cell volume (V) using impedance to direct current discharge and conductivity (C) and light scatter (S) using radiofrequency opacity and laser beam to emphasize the internal structure of the cell. This device analyzes more than 8000 WBCs and gives an average value. This device can also evaluate morphological changes in reactive neutrophils and monocytes based on changes in volume, conductivity and light scatter. Reactive monocyte types and neutrophil left shift can be evaluated by an increase in VCS parameters (10). 

The average size of the circulating neutrophil population is shown by mean neutrophil volume (MNV) (11). It has been suggested that changes in MNV are associated with an increased inflammatory response (11-15) and a marker of disease severity in several infectious diseases and trauma (15). 

Complete blood count is a simple and cheap test performed in all laboratories. Parameters that can be determined by VCS and complete blood count can be evaluated using an easy accessible and inexpensive method by clinicians.

In this study, we aimed to determine changes in VCS parameters in smokers compared to non-smokers.

Methods

This prospective case-control study was conducted in Family Practice Polyclinic of Health Sciences University Konya Training and Research Hospital in July 2019. The patients referring to the polyclinic were informed about the study. Informed consent forms were obtained from the patients who voluntarily accepted to participate in the study according to World Health Union, Helsinki Declaration. Among the volunteers, 117 patients without exclusion criteria were enrolled consecutively into the study. Ethical Committee of KTO Karatay University, Faculty of Medicine approved the study (2019/0038).

The individuals between 18 and 65 years of age were enrolled in the study. While those who smoked at least 10 pack-years were included in the case group, those who never smoked at all were included in the control group. The exclusion criteria were specified as follows: having various diseases (such as any infectious disease in the last month, diabetes mellitus, cancers, cardiovascular, gastrointestinal, pulmonary, renal and neurological diseases) and receiving steroids and immunosuppressive drugs.

Venous blood was drawn into tubes containing ethylenediaminetetraacetic acid (EDTA) as an anticoagulant agent from all participants for complete blood count. Then, they were analyzed using the automated hematology analyzer COULTER LH 780 (Beckman Coulter, Fullerton, CA, USA).

IBM SPSS Statistics for Windows Version 22.0 (Statistical Package for the Social Sciences, IBM Corp., Armonk, NY, USA) program was used for data coding and statistical analysis. While categorical data were expressed as frequency and percentage,  numerical data were expressed as mean ± standard deviation (mean±SD). The Kolmogorov-Smirnov and Shapiro-Wilk tests were used to assess the normality of data. While the Independent Two-Sample T-Test was used for normally distributed continuous data, the Mann-Whitney U Test was used for non-normally distributed continuous data. P-values below 0.05 were considered statistically significant.

Results

A total of 117 individuals (45 smokers and 72 non-smokers) were included in the study. While the case group consisted of 37 men and 8 women, the control group consisted of 34 men and 38 women. There was a statistically significant difference between the case and control groups in terms of gender distribution (p<0.001). 

While there was a statistically significant difference in WBC (p=0.038), hemoglobin (p<0.001), hemotocrit (p<0.001), MCV (p=0.011), lymphocyte (p=0.007), eosinophil (p=0.002), neutrophil (p=0.022), monocyte (p=0.020) values between the two groups, there was no statistically significant difference in age (p=0.653), BMI (p=0.145), RBC (p=0.827), PLT (p=0.250), MPV (p=0.129), RDW (p=0.365) values between the two groups (Table 1).

Table 1. Comparison of hemogram parameters between case and control groups

 

Smokers

(n=45)

Mean ± SD

Non-smokers(n=72)

Mean ± SD

p

Age (years)1

37.52±1.12

37.83±1.03

0.653

BMI2

26.80±0.63

28.63±0.64

0.145

WBC (/mm3)1

8.30±.30

7.34±.17

0.038

RBC (K/ul)1

5.34±.0.07

5.02±.05

0.827

Hb (g/dl)2

15.44±0.21

14.17±0.20

<0.001

Hct (%)2

46.59±0.54

42.69±0.53

<0.001

MCV (fl)2

87.39±0.84

85.15±0.77

0.011

Plt (K/ul)2

236.52±10.54

254.23±8.20

0.250

MPV (fl)2

8.75±0.14

9.03±0.19

0.129

Lymphocyte (/mm3)2

2.45±0.10

2.12±0.06

0.007

Eosinophil(/mm3)2

0.21±0.02

0.13±0.01

0.002

Neutrophil  (/mm3)2

5.06±0.20

4.35±0.18

0.022

Monocyte (/mm3)2

0.62±0.05

0.59±0.08

0.020

RDW (%)

20.76±7.22

13.69±0.12

0.365

1Independent Two-Sample T-Test; 2Mann-Whitney U Test

 

While there was a statistically significant difference in mean neutrophil volume (MNV) (p=0.001), mean neutrophil conductivity (MNC) (p=0.006), mean lymphocyte conductivity (MLC) (p=0.010), mean lymphocyte scatter (MLS) (p=0.045), mean monocyte volume (MMV) (p<0.001), mean monocyte conductivity (MMC) (p=0.011), mean monocyte scatter (MMS) (p=0.018), mean eosinophil conductivity (MEC) (p=0.009) values between the two groups, there was no statistically significant difference in mean neutrophil scatter (MNS) (p=0.135), mean lymphocyte volume (MLV) (p=0.608), mean eosinophil volume (MEV) (p=0.148), mean eosinophil scatter (MES) (p=0. 902) values between the two groups (Table 2).

Table 2: Comparison of VCS parameters between case and control groups

 

Smokers

(n=43)

Mean ± SD

Non-smokers(n=64)

Mean ± SD

p

Neutrophil

Volume (MNV)

147.93±1.25

153.49±1.04

0.001

Conductivity (MNC)

131.81±1.01

136.10±1.10

0.006

Scatter (MNS)

125.58±1.43

1243.43±1.33

0.135

Lymphocyte

Volume (MLV)

81.62±0.72

82.56±0.69

0.608

Conductivity (MLC)

105.93±0.99

110.21±1.11

0.010

Scatter (MLS)

70.00±1.09

73.44±0.97

0.045

Monocyte

Volume (MMV)

165.04±1.62

172.89±1.27

<0.001

Conductivity (MMC)

111.67±1.04

112.54±2.24

0.011

Scatter (MMS)

83.18±0.83

85.61±0.69

0.018

Eosinophil

Volume (MEV)

159.89±1.59

161.03±2.62

0.148

Conductivity (MEC)

134.05±1.00

136.28±2.16

0.009

Scatter (MES)

193.66±0.70

191.16±2.75

0.902

Forty five (38.5%) participants were smokers. Significant differences were found between smoking and non-smoking groups in terms of some hemogram parameters (WBC, hemoglobin, hematocrit, MCV, lymphocyte, eosinophil, neutrophil, monocyte, MNV, MNC, MLC, MLS, MMV, MMC, MMS, MEC) and gender. Bi-nominal logistic regression analysis was performed to evaluate the parameters which independently show smoking state. Logistic regression model was statistically significant (χ2(4) = 56.139, p<0.001). The model explained 51.8% of smoking state (Nagelkerke R2) and classified 80.3% of the cases correctly. Hematocrit, eosinophil, lymphocyte, and MMV were detected as independent parameters for smoking state (Table 3).

Table 3. Detection of the parameters that indicate smoking state independently

 

OR

%95 CI

p

Eozinofil

11.37

3.045-42.459

<0.001

Hematocrit

1.216

1.067-1.385

0.003

Lenfocyte

2.938

1.167-7.395

0.022

MMV

0.896

0.848-0.946

<0.001

Constant

1860.357

0.138

χ2(4) = 56.139, p<0.001

OR=Odds Ratio, CI= Confidence Interval

Discussion

This study quantitatively demonstrated morphological changes in reactive neutrophils, lymphocytes, monocytes and eosinophils in smokers by the VCS technology of the Coulter Hematology Analyzer. This study is the first study in the literature to show morphological changes in reactive neutrophils, lymphocytes, monocytes and eosinophils in smokers by the VCS technology of the Coulter Hematology Analyzer.

Complete blood count is the most important first-line test for evaluation of acute infectious processes requiring early and immediate intervention. Increases in WBC, absolute neutrophil count and neutrophil percentage (especially immature neutrophils [bands]) have been used to predict bacterial infections for a long time (16,17). Automated hematology analyzers can quickly examine a large number of cells to provide comprehensive hematology profiles. Various parameters (such as white blood cell differential count, leukocyte count, red blood cell count, reticulocyte count, and hemoglobin) are obtained (13). Morphological changes in neutrophils, leukocytes, monocytes and eosinophils are quantitatively measured by the VCS technology.

Mardi et al. (13) reported that there was a significant increase in MNV and MMV values in patients with sepsis and localized infection compared to controls. The same researchers also indicated that MNV and MMV can be used to differentiate between sepsis and localized infection. Similarly, Suresh et al. (10) and Celik et al. (18) found that there was a significant increase in MNV and MMV values in bacterial infections.

Zhang et al. (19) reported that total particulate matter (TPM) from cigarette smoke reduced the activity of neutrophils and significantly impaired their bacterial killing activity. Although previous studies argue that natural leukocytes (such as monocytes and neutrophils) first respond to challenges by their limited modulatory roles and memories, recent studies suggest that neutrophils may have more complex programming and memory dynamics (20). Reprogrammed neutrophils with altered functions by TPM may cause host susceptibility to the pathogenesis of chronic diseases (19).

The changes in the hemogram parameters of smokers in our study were consistent with previous studies (6,21,22). Although systemic inflammation increased in smokers, MNV, MNC, MMV and MMC values were found to be statistically significantly lower in smokers compared to non-smokers. This can be attributed to the deterioration of functions of neutrophils and monocytes reprogrammed by chemicals in cigarette smoke. Further studies are needed to explain the mechanism by which smoking leads to changes in VCS parameters.

We could not find any information in the literature about whether VCS parameters are affected by gender. In our study, the percentage of male individuals was significantly higher in the case group than the control group.

Conclusion

This study showed that smoking affected VCS parameters. Clinicians should consider whether the patient smokes if they want to diagnose any diseases using VCS parameters.

References

1. Office of the Surgeon General (US); Office on Smoking and Health (US). The health consequences of smoking: a report of the Surgeon General. Atlanta (GA): Centers for Disease Control and Prevention; 2004. PMID: 20669512

2. Ockene IS, Miller NH. Cigarette smoking, cardiovascular disease, and stroke: a statement for healthcare professionals from the American Heart Association. Circulation. 1997;96(9):3243-7.

3. Wolf PA, D'Agostino RB, Belanger AJ, Kannel WB. Probability of stroke: a risk profile from the Framingham Study. Stroke 1991;22(3):312-8.

4. Yanbaeva DG, Dentener MA, Creutzberg EC, Wesseling G, Wouters EF. Systemic effects of smoking. Chest 2007;131(5):1557-66.

5. Levitzky YS, Guo C-Y, Rong J, Larson MG, Walter RE, Keaney Jr JF, et al. Relation of smoking status to a panel of inflammatory markers: the Framingham offspring. Atherosclerosis 2008;201(1):217-24.

6. Gumus F, Solak I, Eryilmaz M. The effects of smoking on neutrophil/lymphocyte, platelet//lymphocyte ratios. Bratislavske Lekarske Listy 2018;119(2):116-9.

7. Bain B, Rothwell M, Feher M, Robinson R, Brown J, Sever P. Acute changes in haematological parameters on cessation of smoking. Journal of the Royal Society of Medicine 1992;85(2):80.

8. Lee S, Hizoh I, Kovacs A, Horvath Z, Kiss N, Toth-Zsamboki E, et al. Predictors of high on-clopidogrel platelet reactivity in patients with acute coronary syndrome. Platelets 2016;27(2):159-67.

9. Sharma KH, Shah KH, Patel I, Patel AK, Chaudhari S. Do circulating blood cell types correlate with modifiable risk factors and outcomes in patients with acute coronary syndrome (ACS)? Indian Heart Journal 2015;67(5):444-51.

10. SureSh PK, Minal J, Rao PS, Ballal K, Sridevi HB, Padyana M. Volume conductivity and scatter parameters as an indicator of acute bacterial infections by the automated haematology analyser. J Clin Diagn Res 2016;10(1):EC01-3.

11. Bagdasaryan R, Zhou Z, Tierno B, Rosenman D, Xu D. Neutrophil VCS parameters are superior indicators for acute infection. Lab Hematol 2007;13(1):12-6.

12. Bhargava M, Saluja S, Sindhuri U, Saraf A, Sharma P. Elevated mean neutrophil volume + CRP is a highly sensitive and specific predictor of neonatal sepsis. International Journal Of Laboratory Hematology 2014;36(1):e11-4.

13. Mardi D, Fwity B, Lobmann R, Ambrosch A. Mean cell volume of neutrophils and monocytes compared with C‐reactive protein, interleukin‐6 and white blood cell count for prediction of sepsis and nonsystemic bacterial infections. International Journal Of Laboratory Hematology 2010;32(4):410-8.

14. Zhu Y, Cao X, Zhang K, Xie W, Xu D, Zhong C. Delta mean neutrophil volume (ΔMNV) is comparable to procalcitonin for predicting postsurgical bacterial infection. Journal of Clinical Laboratory Analysis 2014;28(4):301-5.

15. Lam SW, Leenen LP, van Solinge WW, Hietbrink F, Huisman A. Comparison between the prognostic value of the white blood cell differential count and morphological parameters of neutrophils and lymphocytes in severely injured patients for 7-day in-hospital mortality. Biomarkers 2012;17(7):642-7.

16. Mathy K, Koepke J. The clinical usefulness of segmented vs. stab neutrophil criteria for differential leukocyte counts. American Journal Of Clinical Pathology 1974;61(6):947.

17. Wenz B, Gennis P, Canova C, Burns ER. The clinical utility of the leukocyte differential in emergency medicine. American Journal Of Clinical Pathology. 1986;86(3):298-303.

18. Celik IH, Demirel G, Aksoy HT, Erdeve O, Tuncer E, Biyikli Z, et al. Automated determination of neutrophil VCS parameters in diagnosis and treatment efficacy of neonatal sepsis. Pediatric Research 2012;71(1):121.

19. Zhang Y, Prasad G, Li L. Suppression of neutrophil antimicrobial functions by total particulate matter from cigarette smoke. Front Immunol 2018;9:2274. doi: 10.3389/fimmu.2018.02274

20. Lee C, Geng S, Zhang Y, Rahtes A, Li L. Programming and memory dynamics of innate leukocytes during tissue homeostasis and inflammation. Journal of Leukocyte Biology 2017;102(3):719-26.

21. Cekici Y, Yilmaz M, Secen O. New inflammatory indicators: association of high eosinophil-to-lymphocyte ratio and low lymphocyte-to-monocyte ratio with smoking. J Int Med Res 2019;47(9):4292–4303.

22. Tulgar Y, Cakar S, Tulgar S, Dalkilic O, Cakiroglu B, Uyanik B. The effect of smoking on neutrophil/lymphocyte and platelet/lymphocyte ratio and platelet indices: a retrospective study. Eur Rev Med Pharmacol Sci 2016;20(14):3112-8.


How to cite / Atıf için: Solak I, Kara A, Öztürk B, Güney I, Eryılmaz MA. Effects of smoking on volume, conductivity and scatter parameters of leukocytes. Euras J Fam Med 2020;9(1):9-14. doi:10.33880/ejfm.2020090102


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